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Table Talk with Mr. Andreas Szakacs

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“You can only become truly accomplished at something you love. Don’t make money your goal. Instead, pursue the things you love doing, and then do them so well that people can’t take their eyes off you.” Become more valuable. Do more. Give more. Be more. Serve more. Mr. Andreas Szakacs from Sweden preached the same philosophy and today stands on top of his game. He started his financial career around 2014 and today, he is the CEO of a FOREX trading platform, a Bank owner, a Venture Capitalist and an enthusiastic traveller.

He has worked extensively with European financial institutions and triumphed in delivering financial advising to East European companies. His intensive experience working with European customers has given Mr. Szakacs a unique vantage point when it comes to figuring out the primary challenges that customers face while transferring money from one country to another. Under his leadership and mentorship, several start-up banks and financial institutions have been able to turn a seemingly impossible idea into a tangible banking system that benefits people around the globe, including developing nations. He is also an avid financial investor in companies from the East European market. Today, we are here to recognize the real man inside the Financial Industry Veteran we all know. Our heartiest indebtedness to Mr. Szakacs for responding to our questions.

What accounts as your biggest accomplishment and what is your prime short-term goal?

I would account Omega Pro via which we helped 1000k people in the financial world. My target is to hit a million satisfied clients by the end of 2021.

What do you consider as your best characteristics?

I know I can be the hardest working person in the room, very patient, and marvelously ambitious.

Are you more inclined to “build your own empire” or unleash the potential of others?

I would unleash the potential of others to help me build my own empire. I appreciate aura, communication skills and presentability of a person more than anything.

Who is your idol in the business field and the supreme teaching you follow?

Mr. Jack Ma, the founder of Ali Baba is my idol. I preach his thought – “No matter how tough the chase is, you should always have the dream you saw on the first day. It’ll keep you

motivated and rescue you”.

If you could change one thing about the world, regardless of guilt or politics, what would you do?

I will turn the globe towards world peace and eradicating poverty. I help organisations like My Big Day and The Fan Foundation to give back to the society.

Would you rather have exceptional wealth or exceptional intelligence?

I would choose exceptional intelligence. I know I can acquire the other with it.

Who is your favourite actor and actress?

I’m a huge fan of the sitcom FRIENDS. My favourite actress is Jennifer Aniston and I love the versatility of Matthew McConaughey.

What is something most people don’t know about you?

I’m ex-military personnel and I have worked as a store manager.

What are your avocations besides work?

 I am an avid traveller and I have visited 40+ countries. I enjoy experiencing different cultures and cuisines. I play polo and cherish long drives. Swimming and diving replenish me.

Rosario is from New York and has worked with leading companies like Microsoft as a copy-writer in the past. Now he spends his time writing for readers of BigtimeDaily.com

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Business

MetaWorx: Building Full-Stack AI Teams, Not Just Automation

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Automation still dominates most headlines, yet the returns often fail to meet expectations. A sprawling chatbot rollout might shave a few support tickets, but it rarely shifts the profit-and-loss statement in a lasting way. 

McKinsey’s 2025 workplace survey pegs AI’s long-term productivity upside at $4.4 trillion, but only one percent of enterprises say they’ve reached true “AI maturity.” MetaWorx, a Dallas, Texas-based AI employee agency founded by Rachel Kite, argues that the shortfall has nothing to do with models and everything to do with people. 

“Treat AI like a point solution and you’ll get point-solution results,” shares Kite. “You need a roster that can carry the ball from raw data to governance, or the whole thing stalls at the proof-of-concept phase.”

The pod blueprint

When a plug-and-play automation script collapsed under real-world data drift, costing Kite a lucrative contract, she sketched the six-person “pod” that now anchors every MetaWorx engagement:

  1. An infrastructure architect to tame compute costs.
  2. A data engineer to secure and shape pipelines. 
  3. An applied scientist to prototype models against live feedback loops. 
  4. An MLOps engineer to automate rollback and retraining. 
  5. A domain product lead translates forecasts into features users actually notice. 
  6. Ethics and compliance analysts to stress test outputs for bias and keep the audit. 

The team’s first sprint still delivers a quick-win bot — “small enough to calm the CFO,” jokes Kite — but the roadmap quickly pivots to reliability, explainability, and eventually optimization. By tying every algorithmic decision to a quantifiable business metric, the pods turn AI from a science project into a growth lever. 

Recruiting for curiosity, not credentials

With Bain & Company predicting a global AI-skills crunch through 2027, MetaWorx has stopped chasing unicorn résumés. Instead, it hires “adjacent athletes”: a computer-vision PhD who hops from medical imaging to warehouse surveillance, or a former journalist who recasts her nose for story into prompt-engineering finesse.

“Domain expertise expires fast,” Kite says. “What doesn’t expire is the instinct to ask better questions.” The result is a lattice of overlapping skills that stays flexible when models wander into the long tail of edge-case data.

A culture of rapid experiments

Inside MetaWorx, every idea faces the same litmus test: ship something — anything — into a user’s hands within 21 days. The “three-week rule” forces prototypes into the wild early, where failure is cheap and feedback is swift. Post-mortems, including cost overruns, are circulated company-wide, erasing any stigma associated with missteps.

That laboratory mindset powers velocity. “Our first model is almost always wrong,” Kite admits, “but version 1.0 is the tuition we pay for version 2.0.” The philosophy echoes her TEDx talk on resilience: progress is iterative, not heroic.

How leaders can steal the playbook

Executives itching to replicate MetaWorx’s results don’t need a blank check. Kite offers a five-step sequence:

  • Inventory pain points, not tools: Walk the P&L line by line and tag the friction you can measure.
  • Map the stack to the problem: A recommendation engine, for instance, requires behavior data, retraining triggers, and feedback capture — automation alone won’t suffice.
  • Stand up a pod: Reassign existing talent into a cross-functional tiger team before hiring externally; the chemistry test is free.
  • Measure the story, not just the statistic: Pair model accuracy with human-scale metrics like ticket backlog or employee churn.
  • Budget for the boring: Reserve at least 30 percent of spend for MLOps and governance; Stanford’s HAI review links most AI failures to neglected upkeep.

Taken together, those steps shift AI from a pilot novelty to an operational habit that compounds value rather than topping out after an initial PR splash.

Character still scales faster than code

MetaWorx plans to double its headcount this year, yet Kite insists the secret isn’t a proprietary framework or a monster war chest. It’s credibility. Clients see a founder who has wrestled with the same outages and surprise bills they face. That authenticity converts skeptics faster than any algorithmic novelty.

“Tools level out,” Kite says. “Culture compounds.”

The insight lands in a marketplace still dazzled by generative fireworks. Yes, MetaWorx ships models and dashboards, but its true product is a mindset: resilience over rigidity, questions over credentials, experiments over edicts. In Kite’s world, automation is merely the appetizer. The main course is a full-stack team that knows why the model matters to the business and who owns its success after launch day.

And that, Kite argues, is how AI finally graduates from cost-cutter to growth engine, one curious pod at a time.

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